1. Field of the Invention
The present invention relates to a digital phased array system and more specifically to digital phased array system parallel architectures for superresolution beamformers.
2 Description of Related Art
Digital phased array systems employ a number of sensors employed over a surface area. At any given instant, information from the phased array can be represented by a large data vector. The large data vectors are accumulated in large order matrix arrays that are manipulated in order to produce solutions. In the case of a radar or sonar system, the solution can be represented by an image which is reconstructed on the display screen. In order to produce finer resolution, a greater number of sensors are used. This results in the larger size matrix arrays to be solved. The computation time required to implement superresolution beamforming with an array of x sensors is usually proportional to x.sup.3. This means that doubling the number of sensors increases the computation by a factor of eight.
There are a number of techniques which are used to avoid large matrix problems. Unfortunately, most of these approaches compromise the potential system resolution. An example would be the division of a large phased array into non-overlapping smaller phased arrays. These subarrays are represented by small matrix arrays, each with sample orders that are small enough to make matrix operations feasible. However, this procedure reduces the Rayleigh resolution to that of the shorter length sub-apertures corresponding to the smaller matrix arrays. (The Rayleigh angular resolution is defined as the carrier wavelength divided by the physical length of the aperture.)
Another technique involves autoregressive parametric analysis. This involves the reduction of the order of parametric models to levels small enough to suppress instabilities. The arithmetic instabilities which are manifested in spurious peaks are caused by large noise-induced fluctuations in the small eigenvalues of the autocorrelation matrices. These methods also significantly degrade resolution.
The problem to be solved is to obtain high, sub-Rayleigh image resolution at moderately low SNR scenarios for phased arrays when the order of the array is too large for the matrix based superresolution methods to be practicable. Here the number of elements in the phased array represent both the order of the array and also the order of the covariance matrices which are computed from the complex elemental data.
There is an extensive prior art associated with multi-rate signal processing architectures as they apply to voice coding (See "A Digital Signal Processing Approach to Interpolation", R.W. Schafer and L.R. Rabiner, Proc. IEEE, Vol. 61, pp. 692-702, Jun. 1973). The generic architecture for the multirate preprocessor of the superresolution systems consists of sequential operations involving the combination of filtering, base band modulation, and decimation which provides a division of the spatial spectrum (often referred to as beam space) into spatial spectral subbands, called sectors. Different architectures which basically accomplish the same end effect correspond to permutations of the order of the signal processing operations.
Superresolution algorithms are the class of algorithms which produce effective pencil beams (angular resolution) which, on the average, are of sub-Rayleigh resolution. Superresolution is often expedited using some form of a matrix approach based upon covariance matrices computed from the elemental complex data for the sampled phased array. Difficulties often occur when the order of the matrices are large, say greater than .about.32. Large matrices are computationally burdensome, and moreover are susceptible to instability problems associated with potential ill-conditioning.
There is a need for an architecture that employs spatial spectral subbanding techniques for the specific purpose of creating effective lower element order pseudo-arrays which can be processed in parallel in a matrix based superresolution algorithms without sacrificing resolution.